Imagine a shopper asks an AI assistant a simple question:
"Find me a product that's actually made in the USA."
The AI checks your listing. The title says "Made in USA." Your bullet points talk about American craftsmanship. But somewhere deeper in the product data, the country of origin says "Imported."
That is exactly the kind of contradiction that should make a seller nervous.
A new study from Columbia Law School's Center for the Law and Economy found that Amazon's Alexa for Shopping and Walmart's Sparky can identify potential conflicts between "Made in USA" claims and country-of-origin information elsewhere in a product listing. The surprising part? The AI assistants may recognize the problem without necessarily warning shoppers about it.
For sellers, that creates a bigger issue than simple listing accuracy. It creates a trust gap.
AI Is Reading Your Listing Differently Than a Shopper
For years, sellers have thought about product pages in terms of what a human shopper sees first.
AI shopping assistants are changing that.
They can compare information across different parts of a listing and identify contradictions that a shopper might never notice. In the Columbia study, researchers found examples where a product was promoted as "Made in USA" while other listing information indicated that it was imported.
That means your product page isn't really one piece of content anymore. It's a collection of data points that AI systems can cross-check.
And if those data points don't agree, your listing could look less trustworthy even if the contradiction was caused by an old attribute, supplier update, or catalog error.
This is where Brand Compliance Monitoring becomes much more important. Instead of checking whether a listing simply contains the right keywords, brands need to make sure the claims, attributes, images, and supporting information all tell the same story.
“Made in USA” Is Not Just Marketing Copy
There is also a legal reason to take this seriously.
The Federal Trade Commission says products advertised as "Made in USA" must generally be "all or virtually all" made in the United States. In July 2025, the FTC sent warning letters to several companies and separately contacted Amazon and Walmart about potentially deceptive U.S.-origin claims from third-party sellers.
Walmart's current Marketplace policy is particularly direct: a Made in USA claim must be consistent across images, packaging, and item attributes. Walmart says listings containing conflicting country-of-origin information can be unpublished.
So if your product says "Made in USA" in one place and "Imported" in another, this isn't something to leave on the "we'll clean it up later" list.
The Bigger Problem Is What AI Does With That Contradiction
Here's where things get interesting.
The Columbia researchers found that both Amazon and Walmart's AI assistants had the technical ability to identify potentially misleading origin claims. Yet the study says the assistants did not consistently flag those discrepancies to shoppers.
That tells sellers something important: AI-powered shopping doesn't automatically mean AI-powered compliance.
An assistant may understand your product perfectly well but still present information selectively.
That creates two separate risks.
Shoppers See an Incomplete Picture
Shoppers could receive incomplete or misleading information about your product.
Competitors Become Easier to Recommend
Another seller with cleaner, more consistent product data could become easier for an AI assistant to recommend.
This is why Brand Protection and Price Control should increasingly include product-content integrity, not just unauthorized sellers and pricing violations.
What Sellers Should Audit Before Q4
You don't need to rebuild every product page from scratch. Start with the claims that matter most.
Check your country-of-origin fields.
Compare the official origin attribute with your title, bullets, description, A+ Content, images, packaging references, and backend catalog data.
Audit every "Made in USA" variation.
Look for phrases such as "Made in America," "Manufactured in USA," "Assembled in USA," or similar language. Walmart's policy specifically addresses several of these claim variations.
Remove outdated supplier information.
A manufacturing change can leave old origin claims sitting inside product copy long after the supply chain has changed.
Check your images, too.
A badge saying "American Made" can create the same problem as a written claim if the underlying product information says something different.
Create one source of truth.
Your product information should be synchronized across marketplaces rather than maintained separately by different teams.
This is exactly the kind of work a Global Ecommerce Accelerator can help organize across multiple marketplaces, especially when brands are managing large catalogs and frequent content updates.
Think Like the AI Shopping Assistant
The easiest test is surprisingly simple.
Take your own product listing and ask an AI shopping assistant questions a customer might ask:
- "Is this product actually made in the USA?"
- "Where is this product manufactured?"
- "Does the country of origin match the product description?"
- "Are there any conflicting claims about where this product is made?"
Then compare the answer with your actual catalog data.
If the AI gets confused, your customer might be confused too.
And as AI becomes a bigger part of product discovery, Brand Compliance Monitoring needs to move beyond checking whether individual fields are technically populated. The goal is consistency across the entire digital shelf.
For brands selling across Amazon, Walmart, and other marketplaces, that is becoming part of Global Ecommerce Accelerator strategy. Clean product data isn't just about avoiding compliance problems. It can influence whether an AI system understands, trusts, and confidently recommends your product.
The brands that get ahead of this won't necessarily be the ones with the longest product descriptions or the most aggressive claims.
They'll be the ones whose product information tells one consistent story, no matter where the shopper or AI looks.
And with AI shopping assistants increasingly sitting between consumers and product pages, that consistency could become one of the most valuable forms of Global Ecommerce Accelerator preparation a seller can make.